pith:OGZLHNUR
Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer
A decoupled surrogate for multi-expert deferral separates class posteriors from expert utilities to eliminate gradient pathologies.
arxiv:2604.09414 v3 · 2026-04-10 · stat.ML · cs.LG
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Record completeness
Claims
The decoupled surrogate is the only method that avoids amplification under redundancy, preserves rare specialists, and consistently improves over a standalone classifier across all settings.
That separating class posterior estimation (softmax) from expert utility estimation (independent sigmoids) removes the amplification, starvation, and coupling pathologies without introducing new failure modes under realistic expert correlation structures.
A decoupled surrogate separates class posterior estimation from per-expert utility estimation, yielding a J-independent H-consistency bound and avoiding the amplification, starvation, and coupling issues of prior augmented-action surrogates.
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Receipt and verification
| First computed | 2026-05-21T01:05:18.754410Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OGZLHNURTYEF2GKLCX47BDMA6Z \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 71b2b3b6919e085d194b15f9f08d80f6479e6192cd5cfd3757ee179d56986a4f
Canonical record JSON
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